Discussion Review- Reading Group 2- Emotion in music and predictive processing

Thanks to all who came along for our second EMPRes session of 2017! It’s always nice to see more faces the second time around, that means we must be doing something right 😉 This week we heard insight from musicians, psychologists, philosophers, and a visiting researcher in cognitive neuroscience who lucky for us chimed in with some ideas regarding this week’s neuroscience paper. For this session, we read the introduction chapter to Huron’s book Sweet Anticipation (2006), Koelsch et al. (2015) neuroscientific overview of emotion with some musical examples, and Gebauer, Kringelbach and Vuust’s (2015) review of Koelsch et al.’s proposed Quartet Theory of Emotion through the lens of predictive processing in music. Below is a review of our discussion, and a summary of the texts can be found here.

*Reminder* Our next meeting is on Thursday March 30th at 1pm in 50 George Square, room 2.3o *note the room change*

ITPRA, the Western art music tradition, and cognitivism

In evaluating the first chapter of Huron’s book, we realized that the groundwork of his ITPRA model was laid out in the context of many expectation-laden events other than music. But that’s okay, since we know where the rest of his text is headed as an explanation of musical expectation.

The ITPRA model aims to explain expectation for events both at a very general, long time frame involving conscious imaginings (such as the expectation of receiving a raise at work), and at specific, short time frames (such as the expectation of the next note or chord in a sequence). With the evolutionary story provided, it is sensed that emotions play[ed] an integral role in forming accurate expectations, and thus enhancing chances for survival. However, the first paragraph of the introduction provides a very offhand account of emotions as potentially frivolous coloring of experience:

Perhaps, while emotions may be beneficial in informing and evaluating expectations/predictions, they may not be altogether necessary. We thought about this a bit more when we discussed emotion’s potential role in predictive coding.

The reference to Meyer’s account of “emotional content of music aris[ing] through the composer’s choreographing of expectation” was also problematic. As pointed out by Nikki, it is important to consider that contrary to the Western art tradition of pre-composed music mediated by a performer, the composer is not always separate from the performer either in body or in time. Not all music is scripted, and improvisatory music-making occurs (is composed by) the performer at the same time that it is being performed. Russ noted that this consideration has been left out in most (all?) of the literature we’ve reviewed so far in this reading group, and it would add clarity if author’s inserted a simple statement along the lines of ‘for the purposes of the current project, we are looking at pre-composed music’ or a claim that their project applies equally well to both pre-composed and improvisatory contexts. As our resident improviser, Russ was asked whether it feels like he is choreographing expectations during an improv performance. Perhaps not in cases of free improvisations, but at say, a wedding, it would be more likely to engage in more melodic ‘performance norms—things that you would expect [at a wedding]’, such as a certain genre, form, style, etc. which ‘fits within the norm’. In other words, context matters.

Coming back to the ITPRA model itself, it does seem quite rooted in the cognitivist paradigm. Especially given there is an entire acronym given for ‘appraisal’, which grants heavy influential capabilities to cognitive evaluations.

The Quartet Theory of Human Emotions

The main conclusion to draw from this model is the reciprocal interactions between effector systems, affect systems, and conscious appraisal systems (such as language), as well as reciprocal interactions within elements of each system. Koelsch et al. provide neurological evidence for the emotional involvement of each of the brain’s four affect systems (orbitofrontal-centered, hippocampus-centered, diencephalon-centered, and brainstem-centered), as informed by the brain’s four effector systems (peripheral arousal, action tendencies, motor expression, and memory & attention). The interaction of these systems leads to an ‘emotion percept’, which consists of four components, an affective component, a sensory-interoceptive component, a motor component, and a cognitive component. The emotion percept is a feeling sensation which is a feeling sensation evoked before any bias from translation into propositional content (words). This conception of a pre-verbal ‘emotion percept’, seems similar to what Ian Cross terms ‘floating intentionality’, referring to music’s general ‘aboutness’ which is the agreed meaningfulness attributed to music without mutual agreement on specifically what that meaning is.

“music’s inexpliciteness, its ambiguity or floating intentionality may thus be regarded as a highly advantageous characteristic of its function for groups; music, then, might serve as a medium for the maintenance of human social flexibility” –Cross 2004

Predictive coding accounts of music, is emotion necessary?

In Gebauer, Kringelbach, and Vuust’s review of the Quartet Theory of Human Emotions from the lens of predictive coding, claiming that emotion could be the weight/modulator of prediction error itself, guiding behavior, action, and learning. Perhaps rather than (or in addition to) a modular influence of a global emotion (such as joy, or anger), it may be useful to consider a hierarchy of different neurons having a particular valence. Perhaps at the lowest level there would be a binary Y/N (good/bad) valence receptive field, and the next level may consist of neurons which respond to populations of lower-level neurons (in the same manner as retinal ganglion cells responding preferentially to certain orientations of lines; and even incorporating something similar to center-surround style activation to either facilitate or inhibit response). More complex emotions (what we may be cognitively aware of) would arise as a result of a hierarchy of these valence responses at differing levels of complexity.

However, Lauren brought up a good point, why is emotion even necessary in this prediction and prediction error model? It may seem like a useful and exciting way to account for emotions as modulations of prediction error, and a motivational factor for making accurate predictions, however the predictive coding model seems to work just fine without attempting to squeeze emotions into the mix. And indeed, seeking to define emotions because ‘we know we have emotions’ is a lot like examining the pineal gland searching for the soul because ‘we know we have souls’.

*Reminder* Our next meeting is on Thursday March 30th at 1pm in 50 George Square, room 2.3o *note the room change*